Computational Linguistics and Intelligent Text Processing

1. Front Matter

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2. General Techniques

   1. Unsupervised Feature Adaptation for Cross-Domain NLP with an Application to Compositionality Grading

      • Lukas Michelbacher, Qi Han, Hinrich Schütze

      Pages 1-12

   2. Syntactic Dependency-Based N-grams: More Evidence of Usefulness in Classification

      • Grigori Sidorov, Francisco Velasquez, Efstathios Stamatatos, Alexander Gelbukh, Liliana Chanona-Hernández

      Pages 13-24

3. Lexical Resources

   1. A Quick Tour of BabelNet 1.1

      • Roberto Navigli

      Pages 25-37

   2. Automatic Pipeline Construction for Real-Time Annotation

      • Henning Wachsmuth, Mirko Rose, Gregor Engels

      Pages 38-49

   3. A Multilingual GRUG Treebank for Underresourced Languages

      • Oleg Kapanadze, Alla Mishchenko

      Pages 50-59

   4. Creating an Annotated Corpus for Extracting Canonical Citations from Classics-Related Texts by Using Active Annotation

      • Matteo Romanello

      Pages 60-76

   5. Approaches of Anonymisation of an SMS Corpus

      • Namrata Patel, Pierre Accorsi, Diana Inkpen, Cédric Lopez, Mathieu Roche

      Pages 77-88

   6. A Corpus Based Approach for the Automatic Creation of Arabic Broken Plural Dictionaries

      • Samhaa R. El-Beltagy, Ahmed Rafea

      Pages 89-97

   7. Temporal Classifiers for Predicting the Expansion of Medical Subject Headings

      • George Tsatsaronis, Iraklis Varlamis, Nattiya Kanhabua, Kjetil Nørvåg

      Pages 98-113

   8. Knowledge Discovery on Incompatibility of Medical Concepts

      • Adam Grycner, Patrick Ernst, Amy Siu, Gerhard Weikum

      Pages 114-125

   9. Extraction of Part-Whole Relations from Turkish Corpora

      • Tuğba Yıldız, Savaş Yıldırım, Banu Diri

      Pages 126-138

   10. Chinese Terminology Extraction Using EM-Based Transfer Learning Method

       • Yanxia Qin, Dequan Zheng, Tiejun Zhao, Min Zhang

       Pages 139-152

   11. Orthographic Transcription for Spoken Tunisian Arabic

       • Inès Zribi, Marwa Graja, Mariem Ellouze Khmekhem, Maher Jaoua, Lamia Hadrich Belguith

       Pages 153-163

4. Morphology and Tokenization

   1. An Improved Stemming Approach Using HMM for a Highly Inflectional Language

      • Navanath Saharia, Kishori M. Konwar, Utpal Sharma, Jugal K. Kalita

      Pages 164-173

   2. Semi-automatic Acquisition of Two-Level Morphological Rules for Iban Language

      • Suhaila Saee, Lay-Ki Soon, Tek Yong Lim, Bali Ranaivo-Malançon, Enya Kong Tang

      Pages 174-188

   3. Finite State Morphology for Amazigh Language

      • Fatima Zahra Nejme, Siham Boulaknadel, Driss Aboutajdine

      Pages 189-200

   4. New Perspectives in Sinographic Language Processing through the Use of Character Structure

      • Yannis Haralambous

      Pages 201-217

   5. The Application of Kalman Filter Based Human-Computer Learning Model to Chinese Word Segmentation

      • Weimeng Zhu, Ni Sun, Xiaojun Zou, Junfeng Hu

      Pages 218-230

   6. Machine Learning for High-Quality Tokenization Replicating Variable Tokenization Schemes

      • Murhaf Fares, Stephan Oepen, Yi Zhang

      Pages 231-244

This two-volume set, consisting of LNCS 7816 and LNCS 7817, constitutes the thoroughly refereed proceedings of the 13th International Conference on Computer Linguistics and Intelligent Processing, CICLING 2013, held on Samos, Greece, in March 2013. The total of 91 contributions presented was carefully reviewed and selected for inclusion in the proceedings. The papers are organized in topical sections named: general techniques; lexical resources; morphology and tokenization; syntax and named entity recognition; word sense disambiguation and coreference resolution; semantics and discourse; sentiment, polarity, subjectivity, and opinion; machine translation and multilingualism; text mining, information extraction, and information retrieval; text summarization; stylometry and text simplification; and applications.

• controlled natural language
• dependency grammar
• multilingual ontologies
• semantic networks
• unsupervised learning

• Center for Computing Research, National Polytechnic Institute, Mexico D.F., Mexico

  Alexander Gelbukh

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